https://scholars.lib.ntu.edu.tw/handle/123456789/489252
標題: | Job sequence scheduling for cloud computing | 作者: | Hsu, Y.-C. Liu, P. PANGFENG LIU |
公開日期: | 2011 | 起(迄)頁: | 212-219 | 來源出版物: | Proceedings - 2011 International Conference on Cloud and Service Computing, CSC 2011 | 摘要: | This paper describes the important issue of energy conservation for data centers. We consider the problem of provisioning physical servers to a sequence of jobs, and reducing the total energy consumption. The performance metric is the wasted energy - the over-provisioned computing power provided by the physical servers, but exceeding the requirement of the jobs. We propose three new strategies for allocating servers to a sequence of jobs - a largest machine first heuristic, a best fit method, and a mixed method. We prove that both the largest machine first heuristic and the mixed method will only incur at most 2 in over-provisioned energy. That is, the ratio between the over-provisioned energy and the total provisioned energy is bounded by 2/n(1 + δ), where n is the number of jobs, and 1 + δ is the ratio between the maximum and minimum execution time of jobs. We also derive a tight bound of i on the ratio of wasted energy if the ratio δ could be arbitrarily large. We also conduct experiments to compare the three algorithms in practice. The experiment results indicate that all three algorithms waste very little energy in over-provision. The mixed method outperforms the best fit method, which outperforms the largest machine first method. © 2011 IEEE. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/489252 | DOI: | 10.1109/CSC.2011.6138524 | SDG/關鍵字: | Best fit; Computing power; Data centers; Execution time; Job sequences; Mixed method; New strategy; Performance metrices; Tight bound; Total energy consumption; Algorithms; Cloud computing; Energy conservation; Energy conversion; Energy utilization; Experiments; Scheduling; Heuristic methods |
顯示於: | 資訊工程學系 |
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